ABSTRACT
Our guest this episode is Glenn Jocher, CEO and founder of Ultralytics, the company that brought you YOLO v5 and v8. Gil and Glenn discuss how to build an open-source community on Github, the history of YOLO and even particle physics. They also talk about the progress of AI, diffusion and transformer models and the importance of simulated synthetic data today. The first episode of season 2 is full of stimulating conversation to understand the applications of YOLO and the impact of open source on the AI community. TOPICS & TIMESTAMPS

0:00 Introduction
2:03 First Steps in Machine Learning
9:40 Neutrino Particles and Simulating Neutrino Detectors
14:18 Ultralytics
17:36 Github
21:09 History of YOLO
25:28 YOLO for Keypoints
29:00 Applications of YOLO
30:48 Transformer and Diffusion Models for Detection
35:00 Speed Bottleneck
37:23 Simulated Synthetic Data Today
42:08 Sentience of AGI and Progress of AI
46:42 ChatGPT, CLIP and LLaMA Open Source Models
50:04 Advice for Next Generation CV Engineers

LINKS & RESOURCES

Linkedin

Twitter

Google scholar 

Ultralytics

Github

National Geospatial Intelligence Agency

Neutrino

Antineutrino

Joseph Redmon

Ali Farhadi

Enrico Fermi

Kashmir World Foundation

R-CNN

Fast R-CNN

LLaMA model

MS COCO

GUEST BIO

Glenn Jocher is currently the founder and CEO of Ultralytics, a company focused on enabling developers to create practical, real-time computer vision capabilities with a mission to make AI easy to develop. He has built one of the largest developer communities on GitHub in the machine learning space with over 50,000 stars for his YOLO v5 and YOLO v8 releases. This is one of the leading packages used for the development of edge device computer vision with a focus on object classification, detection, and segmentation at real-time speeds with limited compute resources. Glenn previously worked at the United States National Geospatial Intelligence Agency and published the first ever Global Antineutrino map. 

ABOUT THE HOST:

I’m Gil Elbaz, co-founder and CTO of Datagen. In this podcast, I speak with interesting computer vision thinkers and practitioners. I ask the big questions that touch on the issues and challenges that ML and CV engineers deal with every day. On the way, I hope you uncover a new subject or gain a different perspective, as well as enjoying engaging conversation. It’s about much more than the technical processes – it’s about people, journeys, and ideas. Turn up the volume, insights inside.